Reinforcement learning on an omnidirectional mobile robot
نویسندگان
چکیده
With this paper we describe a well suited, scalable problem for reinforcement learning approaches in the field of mobile robots. We show a suitable representation of the problem for a reinforcement approach and present our results with a model based standard algorithm. Two different approximators for the value function are used, a grid based approximator and a neural network based approximator.
منابع مشابه
Path Following and Velocity Optimizing for an Omnidirectional Mobile Robot
In this paper, the path following controller of an omnidirectional mobile robot (OMR) has been extended in such a way that the forward velocity has been optimized and the actuator velocity constraints have been taken into account. Both have been attained through the proposed model predictive control (MPC) framework. The forward velocity has been included into the objective function, while the a...
متن کاملDynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملReinforcement Learning based Omnidirectional Vision Agent for Mobile Robot Navigation
This paper presents an Omnidirectional Vision Agent able to learn to navigate a mobile robot in its working environment. The novelty of the work is the application of Reinforcement Learning paradigm to Vision Agents aiming to develop a totally autonomous system able to learn control policies by on-line learning, to deal with changing environment and to improve its performance during lifetime. S...
متن کاملRobot docking based on omnidirectional vision and reinforcement learning
We present a system for visual robotic docking using an omnidirectional camera coupled with the actor critic reinforcement learning algorithm. The system enables a PeopleBot robot to locate and approach a table so that it can pick an object from it using the pan-tilt camera mounted on the robot. We use a staged approach to solve this problem as there are distinct sub tasks and different sensors...
متن کاملVisual Tracking using Learning Histogram of Oriented Gradients by SVM on Mobile Robot
The intelligence of a mobile robot is highly dependent on its vision. The main objective of an intelligent mobile robot is in its ability to the online image processing, object detection, and especially visual tracking which is a complex task in stochastic environments. Tracking algorithms suffer from sequence challenges such as illumination variation, occlusion, and background clutter, so an a...
متن کامل